Improve or Approximation of Nuclear Reaction Cross Section Data Using Artificial Neural Network

Capali, Veli

doi:10.1007/978-3-030-36178-5_82

Improve or Approximation of Nuclear Reaction Cross Section Data Using Artificial Neural Network

Veli Capali ORCID: orcid.org/0000-0002-9045-0210⁴

Conference paper
First Online: 03 January 2020

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Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 43))

Abstract

In this study; discusses the using artificial neural networks for approximation of data such as the nuclear reaction cross sections data. The rate of approximation of the fitting criteria is determined by using the experimental and evaluated data. The some reactions cross-section are calculated from data obtained using neural networks. The results show the effectiveness and applicability of this new technique in the calculation of the some nuclear reactions.

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Authors and Affiliations

Usak University, 64200, Usak, Turkey
Veli Capali

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Veli Capali
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Correspondence to Veli Capali .

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Editors and Affiliations

Department of ECE, Karunya University, Coimbatore, Tamil Nadu, India
D. Jude Hemanth
Department of Computer Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Isparta, Turkey
Utku Kose

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Capali, V. (2020). Improve or Approximation of Nuclear Reaction Cross Section Data Using Artificial Neural Network. In: Hemanth, D., Kose, U. (eds) Artificial Intelligence and Applied Mathematics in Engineering Problems. ICAIAME 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 43. Springer, Cham. https://doi.org/10.1007/978-3-030-36178-5_82

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DOI: https://doi.org/10.1007/978-3-030-36178-5_82
Published: 03 January 2020
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36177-8
Online ISBN: 978-3-030-36178-5
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